Practical Considerations and Strategies for Executing Adaptive Clinical Trials

Weili He, O. Kuznetsova, M. Harmer, C. Leahy, K. Anderson, Nicole Dossin, Lina Li, J. Bolognese, Y. Tymofyeyev, Jerald S. Schindler
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引用次数: 16

Abstract

There is great potential for clinical trials designed with adaptive features to result in more efficient decision making within a drug development program. However, clinical trials with adaptive features are more complex to implement than traditional designs such as fixed-sample or group sequential. Workarounds and/or inefficiencies in adaptive design (AD) trial execution may result in human and material wastes. Further, they may result in the introduction of operational biases that may potentially negate any gains in designing an AD trial and may even render trial results not interpretable. In this article, we present and share our experience and best practices in AD trial implementation in the areas of resource planning, randomization considerations including the importance of randomization schemes on clinical supply, Interactive Voice Randomization System vendor capability assessment and quality control, clinical supply strategy considerations, enrollment management and patient enrollment modeling and simulation, data quality and interim analysis planning, managing blinding and unblinding, and the use of a data monitoring committee.
实施适应性临床试验的实际考虑和策略
具有适应性特征的临床试验设计具有很大的潜力,可以在药物开发计划中产生更有效的决策。然而,具有自适应特征的临床试验比传统设计(如固定样本或群体序列)更复杂。适应性设计(AD)试验执行中的变通方法和/或效率低下可能导致人力和材料浪费。此外,它们可能导致引入操作偏差,这可能会潜在地抵消设计AD试验的任何收益,甚至可能使试验结果无法解释。在本文中,我们将从资源规划、随机化考虑(包括随机化方案对临床供应的重要性)、交互式语音随机化系统供应商能力评估和质量控制、临床供应策略考虑、入组管理和患者入组建模和模拟、数据质量和中期分析规划等方面介绍并分享我们在AD试验实施中的经验和最佳实践。管理盲化和解盲化,以及数据监控委员会的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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